The advent of the hardware of massively extendible media, transport and communications in the 20th century (radio, telephones, automobiles, cargo transport, television, satellite, computing, internet, gps) combined with the refining of Frederick Taylor’s line assembly and “scientific management” methods that allowed for mass production, embedded research & development (R&D), supply chain management and complex operations by massive industrial and consumer-oriented conglomerated (i.e. Walmart, Nissan, Mitsubishi Heavy Industries, Rio Tinto etc). This dual development from the 1950s onward led to a late 20th century consumerist climax, as celebrated in late 1980s and early 1990s pop culture and the later 1990s’ pessimistic rejection of mass consumerism (think: The Matrix, Fight Club etc), which can be considered a “Third Industrial Revolution”.
In the 2000, the climax was peaked. “Irrational Exuberance” over the extent of continuation of the neoliberal model with the West consuming Eastern-produced goods, was realised when the “Dotcom Bubble” crashed in a dramatic way. Infamous companies such as “Pets.Com”, which had been heavily promoted by keen investors who believed that the consumption boom would continue forever, collapsed almost overnight. After September 11 2001, security and geopolitical risks have further sobered global investors’ views of an increasing consumerist boom facilitated by the technological facilities allowed by the advent of the aforementioned mass production and mass consumption technologies.
Nevertheless, the popularisation of a variety of a new set of “fourth industrial revolution”, whose technological footprint was laid in the 1970s-2000s, is promising a further unleashing of consumer activity and investor confidence; albeit in a more equally distributed manner around global growth areas, not simply in America, Japan and Europe. Briefly, there are three of the major upcoming disruptive technologies:
- This is already coming into use in the form of augmented and virtual reality googles, headsets and tools. The key point here is the loss of fixed screens, laptops and interaction modules, in favour of simulated environments.
- Of course, people will continue to enjoy running in the park, talking with one another, and playing together physically but the ease of these technologies means that much social and economic interaction will be heavily disrupted.
- As an example, the simple act of shopping may change, as consumers stop entering shops physically and instead interact with virtual shopping spaces, with the goods being ordered and delivered independently.
- As with the hyper-real tech, this is also already a popular technology, as seen in the continuing success of blockchain technologies (with Bitcoin being a particular famous example), self-driving cars and various upcoming automated systems such as delivery drones and “smart” home appliances.
- This will again simply quicken the link between the consumer and the production and transportation of goods (i.e. the production and supply chain).
- AI is a harder technology to refine. There are two types of AI: Soft and Hard.
- Soft AI is what most people think of when they think of AI. This relates providing machines a means of learning how to make decisions for themselves. This is what we think of when self-driving cars are learning rules about the roads , and communication with millions of other data points to increase the “hive mind” of learning. Another great example of this is Google’s search engine, or Amazon’s Alexa. By feeding more data, including errors, into the “hive mind” the AI improves. Yet it is always at the mercy of human correction and direction since it cannot make self-reflexive decisions.
- Hard AI is much tougher, perhaps even impossible, to achieve. It consists of a machine being able to program itself in such a way as to become imperceptible from other complex sentient beings such as humans. As the various self-driving car crashes have shown, this is particularly difficult because our human brains are uniquely capable of making distinctions, including moral ones, that a machine finds hard to logically replicate. This theme is well discussed in Philip K. Dick’s novel Do Androids Dream of Electric Sheep? and the subsequent movies Blade Runner and Blade Runner 2049.
- This is the trickiest of the new technologies, the one which will take the longest to achieve, and also the most disruptive of them.
- The computer or mobile device that you are reading this on is using a binary code to interpret a set code that “embeds” reality into a string of information to be decoded. For instance, when you call someone on skype, your voice pattern is being transcribed as a set of binary code to be described on the other end; this happens in milliseconds. Similarly, and more importantly for geopolitics, a military operation or communication is organised and discussed using this system, albeit with a heavy encryption that further encodes the binary in a layer of complex and almost unbreakable random strings of numbers and letters (as is also used in most email accounts now, for instance).
- Quantum coding, in theory, would change this completely by simply producing versions of reality in a set of formulaic descriptions. This cuts out the lengthy code, meaning there is much less time taken to send the information, and it also allows for alternative realities to be described, thus enabling a level of “encryption” which is literally unbreakable since the information contained in the alternatives is simply incorrect and unrelated to the “real reality” of the information.
- Of course, a next step after that would be the formulation of alternative realities themselves, one can imagine in a few hundred years that a simulation world like The Matrix may in fact be created without great effort.
- In the meantime, the primary researchers of these technologies are the militaries of China, Russia and the U.S. since their role in disrupting the balance of power of missile, aircraft and communications technologies today is evident.